Work

Time-optimal obstacle avoidance of autonomous ship based on nonlinear model predictive control

Year: 2022

Type: article

Abstract: Autonomous shipping has been identified as the way forward in the maritime transport. However, the time-optimal path planning, anti-disturbance trajectory tracking and obstacle avoidance are still ongoing challenging problems, which have not been properly addressed for autonomous ship. To fill the knowledge gap, we propose a novel nonlinear model predictive control (MPC), which integrates the time-optimal path planning, anti-disturbance tracking and obstacle avoidance. The proposed controller is designed as a 2-level hierarchical controller. In the high level, a planned path considering time minimum and obstacle avoidance is generated by nonlinear MPC in spatial formulation. A spatial reformulation is adopted to express manoeuvring time as a function mathematically. In the spatial coordinate, the manoeuvring time is minimised by MPC to generate a reference path for tracking. In the low level, vessel tracks the time-optimal planning trajectory by nonlinear MPC with extended Kalman filter in temporal formulation. The deviation of the tracking path in longitudinal direction is 15% ship length and the deviation in width direction is 1% under disturbances. The obstacle avoidance is implemented by using the proposed control method, and the tolerance of obstacle avoidance is 2 L (ship length) to meet the safety requirement.

Source: Ocean Engineering

DOI: 10.1016/j.oceaneng.2022.112591

Authors: Ming Zhang, Shuai Hao, Defeng Wu, Ming-Lu Chen, Zhi-Ming Yuan

Institutions: University of Strathclyde, Tianjin University of Technology, Jimei University, Jiangsu University of Science and Technology

Language: English

Topic: Maritime Navigation and Safety

Subfield: Ocean Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,650

Funders: National Natural Science Foundation of China, China Scholarship Council